Kirkpatrick M, Lofsvold D
Department of Zoology, University of Texas, Austin 78712.
Genome. 1989;31(2):778-83. doi: 10.1139/g89-137.
Growth trajectories differ from many other quantitative characters in that they are characterized by a continuous function rather than by a finite number of discrete measurements. We review here recently developed methods for predicting the evolution of growth trajectories under the influence of natural or artificial selection. Using our method, analysis of genetic data from mice shows that the patterns of genetic variation arising from developmental processes impose constraints on evolution of growth trajectories. These constraints can be quantified to reveal the families of growth trajectories that can be produced by selection and those families that cannot. The data suggest there may be relatively few evolutionary degrees of freedom for growth trajectories despite the presence of abundant additive genetic variation to alter size and (or) growth rate at every age. The description of these constraints may be useful to both biologists who would like to determine the evolutionary options available to natural populations and to breeders who would like to alter growth trajectories to economically improve domesticated species. Our methods and conclusions can be generalized to other kinds of "infinite-dimensional" or complex characters, including morphological shapes and norms of reaction.
生长轨迹与许多其他数量性状不同，其特点是由连续函数表征，而非有限数量的离散测量值。我们在此回顾最近开发的用于预测在自然或人工选择影响下生长轨迹演变的方法。使用我们的方法，对小鼠遗传数据的分析表明，发育过程产生的遗传变异模式对生长轨迹的进化施加了限制。这些限制可以量化，以揭示可通过选择产生的生长轨迹类别以及那些无法产生的类别。数据表明，尽管存在丰富的加性遗传变异以改变每个年龄的大小和（或）生长速率，但生长轨迹的进化自由度可能相对较少。这些限制的描述对于希望确定自然种群可用进化选项的生物学家以及希望改变生长轨迹以经济地改良驯化物种的育种者可能都有用。我们的方法和结论可以推广到其他类型的“无限维”或复杂性状，包括形态形状和反应规范。
